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Phi 3 Mini 4K Instruct GGUF by SanctumAI

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  Code   Conversational   En   Endpoints compatible   Gguf   Instruct   Phi3   Quantized   Region:us

Phi 3 Mini 4K Instruct GGUF Benchmarks

LLME Score: 0.22712
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

Phi 3 Mini 4K Instruct GGUF Parameters and Internals

Model Type 
text generation
Additional Notes 
Model quantized by SanctumAI.
Training Details 
Data Sources:
synthetic data, filtered publicly available websites
Methodology:
supervised fine-tuning, direct preference optimization
Context Length:
4000
Input Output 
Input Format:
<|system|> {system_prompt}.<|end|> <|user|> {prompt}<|end|> <|assistant|>
LLM NamePhi 3 Mini 4K Instruct GGUF
Repository 🤗https://huggingface.co/SanctumAI/Phi-3-mini-4k-instruct-GGUF 
Base Model(s)  Phi3AdapterModel   Frinkles/Phi3AdapterModel
Required VRAM1.4 GB
Updated2024-11-21
MaintainerSanctumAI
Model Typephi3
Instruction-BasedYes
Model Files  1.4 GB   2.1 GB   2.0 GB   1.7 GB   2.2 GB   2.4 GB   2.4 GB   2.4 GB   2.2 GB   2.6 GB   2.9 GB   2.8 GB   2.8 GB   2.6 GB   3.1 GB   4.1 GB   7.6 GB   7.6 GB
Supported Languagesen
GGUF QuantizationYes
Quantization Typegguf
Model ArchitectureAutoModel
Licensemit
Phi 3 Mini 4K Instruct GGUF (SanctumAI/Phi-3-mini-4k-instruct-GGUF)

Best Alternatives to Phi 3 Mini 4K Instruct GGUF

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Context / RAM
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...ixtral 8x7B Instruct V0.1 GGUF0K / 15.6 GB44016604
Dolphin 2.5 Mixtral 8x7b GGUF0K / 15.6 GB10071295
Dolphin 2.7 Mixtral 8x7b GGUF0K / 15.6 GB11177134
Spydaz Web AI 0K / 4.4 GB1373
Mixtral AI Llava 4bit0K / 14.4 GB19211
...i 3 Mini 4K Instruct V0.3 GGUF0K / 1.4 GB2275
Phi 3 Mini 4K Instruct0K / 2.3 GB250
Dolphin 2 6 Phi 2 GGUF0K / 1.2 GB613770
Dre Phi Gguf0K / 2.3 GB150
...i 3 Mini 4K Instruct V0.2 GGUF0K / 1.4 GB1462
Note: green Score (e.g. "73.2") means that the model is better than SanctumAI/Phi-3-mini-4k-instruct-GGUF.

Rank the Phi 3 Mini 4K Instruct GGUF Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
Censorship and Alignment  
Data Analysis and Insight Generation  
Text Generation  
Text Summarization and Feature Extraction  
Code Generation  
Multi-Language Support and Translation  

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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241110
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